Investigating associations between maternal stress, smoking and adverse birth outcomes: evidence from the All Our Families cohort
Bibliographic record
Abstract
BACKGROUND: Independently, active maternal and environmental tobacco smoke exposure and maternal stress have been linked to an increased risk of preterm birth and low birth weight. An understudied relationship is the potential for interactive effects between these risk factors. METHODS: Data was obtained from the All Our Families cohort, a study of 3,388 pregnant women < 25 weeks gestation recruited from those receiving prenatal care in Calgary, Canada between May 2008 and December 2010. We investigated the joint effects of active maternal smoking, total smoke exposure (active maternal smoking plus environmental tobacco smoke) and prenatal stress (Perceived Stress Scale, Spielberger State-Trait Anxiety Inventory), measured at two time points (< 25 weeks and 34-36 weeks gestation), on preterm birth and low birth weight. RESULTS: A marginally significant association was observed with the interaction active maternal smoking and Spielberger State-Trait Anxiety Inventory scores in relation to low birth weight, after imputation (aOR = 1.02, 95%CI: 1.00-1.03, p = 0.06). No significant joint effects of maternal stress and either active maternal smoking or total smoke exposure with preterm birth were observed. Active maternal smoking, total smoke exposure, Perceived Stress Scores, and Spielberger State-Trait Anxiety Inventory scores were independently associated with preterm birth and/or low birth weight. CONCLUSIONS: Findings indicate the role of independent effects of smoking and stress in terms of preterm birth and low birthweight. However, the etiology of preterm birth and low birth weight is complex and multifactorial. Further investigations of potential interactive effects may be useful in helping to identify women experiencing vulnerability and inform the development of targeted interventions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".